Abstract

We study the relationship between local structural ordering and dynamical heterogeneities in a model glass-forming liquid, the Wahnström mixture. A novel cluster-based approach is used to detect local energy minimum polyhedral clusters and local crystalline environments. A structure-specific time correlation function is then devised to determine their temporal stability. For our system, the lifetime correlation function for icosahedral clusters decays far slower than for those of similarly sized but topologically distinct clusters. Upon cooling, the icosahedra form domains of increasing size and their lifetime increases with the size of the domains. Furthermore, these long-lived domains lower the mobility of neighboring particles. These structured domains show correlations with the slow regions of the dynamical heterogeneities that form on cooling towards the glass transition. Although icosahedral clusters with a particular composition and arrangement of large and small particles are structural elements of the crystal, we find that most icosahedral clusters lack such order in composition and arrangement and thus local crystalline ordering makes only a limited contribution to this process. Finally, we characterize the spatial correlation of the domains of icosahedra by two structural correlation lengths and compare them with the four-point dynamic correlation length. All the length scales increase upon cooling, but in different ways.

Received 16 October 2012Accepted 23 January 2013Published online 14 February 2013

Acknowledgments:

We thank M. Leocmach for his kind help in bond orientational order analysis and its comparison with TCC analysis. A.M. is funded by Engineering and Physical Sciences Research Council (EPSRC(GB)) Grant No. EP/E501214/1. C.P.R. thanks the Royal Society for funding. H.T. acknowledges support from a grant-in-aid from the Ministry of Education, Culture, Sports, Science and Technology, Japan and the Aihara Project, the FIRST program from JSPS, initiated by CSTP. This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol.